One-step ahead sequential Super Learning from short times series of many slightly dependent data, and anticipating the cost of natural disasters
大量弱依赖数据短序列的单步超学习及自然灾害成本预测
Suppose that we observe a short time series where each time-t-specific data-structure consists of many slightly dependent data indexed by a and that we want to estimate a feature of the law of the experiment that depends neither on t nor on a. We develop and study an algorithm to learn sequentially which base algorithm in a user-supplied collection best carries out the estimation task in terms of excess risk and oracular inequalities. The analysis, which uses dependency…